Background. Infertility is a major reproductive health concern, and barriers to accessing and utilizing infertility treatment services may lead to significant individual and societal consequences. This study aimed to identify the barriers to accessing and utilizing infertility treatment services among infertile women and to propose policy options to address these challenges. Methods. This policy brief was developed based on a multi-phase study employing a mixed (quantitative-qualitative) approach, which included a narrative review study of the available evidence, a descriptive cross-sectional study examining the status of infertile women referring to public and private infertility treatment centers in Tehran (n = 450), and finally, a focus group discussion study aimed at obtaining the opinions of experts in the field of infertility. Results. The major barriers identified included financial constraints and inadequate insurance coverage, geographic accessibility limitations, challenges related to service delivery, insufficient awareness among couples, certain shortcomings in service quality, and individual and cognitive factors affecting treatment continuation. Based on these findings, four policy options were proposed: expanding insurance coverage for infertility services, developing infertility treatment centers, improving the quality of infertility care, and strengthening educational and awareness-raising programs. Conclusion. The findings of this study suggest that treatment costs and inadequate financial support are among the most significant barriers to accessing and utilizing infertility treatment services among infertile women in Tehran. Policy interventions focusing on enhanced insurance coverage, improved geographic access, better quality of care, and increased awareness may help reduce these barriers and improve the utilization of infertility services. Research Insights · Infertility is one of the important issues in reproductive health, and barriers to access to and utilization of treatment services can have considerable individual and social consequences. · Sufficient evidence was lacking regarding the barriers to access to and utilization of infertility treatment services by infertile women, as well as effective policy options for addressing them. · This study, employing a mixed-methods approach, identified the main barriers (financial, insurance-related, geographical, service quality, awareness, and individual factors) and presented four policy options to address them. · By documenting the identified barriers and providing specific policy recommendations, this article filled the scientific gap at the level of problem recognition and solution provision, although it did not assess the effectiveness of the implementation of these policies.
Background. Complete physical, mental, and social health is largely rooted in parenting approaches, but it is not the only influencing factor. This study aimed to explore the optimal parenting style, introduce new and different parenting styles, and the impact of generational change on the adoption of dominant parenting style, with a particular emphasis on cultural factors. The analysis is framed within the context of critiques of classical parenting theories. Methods. This narrative review involved a systematic search of reputable databases, including PubMed, ScienceDirect, and Google Scholar, for English-language articles published between 2005 and 2025. The search terms included parenting styles, parenting, child rearing, Baumrind, and culture. In total, 5791 articles were identified and through several stages of screening, 24 articles were selected for inclusion in the review. Results. The findings suggested that the selection of an optimal parenting style is influenced by highly complex factors, including social context, culture, ideology, ethnicity, and geographical factors,and no single approach can be universally applied across diverse cultural contexts. Furthermore, new parenting styles, distinct from classical models, may emerge in different cultures. Intergenerational research also revealed that contemporary parents are more inclined than previous generations to adapt their parenting styles to align with their children’s needs. Conclusion. The findings of this narrative review indicate that universal and fixed approaches to parenting (e.g. Baumrind parenting styles) have limited applicability. Parenting models need to be reconceptualized within cultural contexts and across generations. Accordingly, adopting flexible and culture-sensitive frameworks may provide more effective guidance for educational, clinical, and policy-related interventions, ultimately enhancing parent–child adaptation in contemporary societies. Research Insights · Neglecting cultural contexts in educational and clinical interventions may lead to increased high-risk behaviors, mental disorders, and healthcare costs. · Classical parenting styles (e.g., Baumrind's model) have limited efficacy in non-Western cultures due to the neglect of cultural differences and intergenerational changes. · Cultural differences in the interpretation of parental behaviors have direct implications for children's mental, social, and physical health. · Designing flexible and culturally sensitive parenting models can serve as an effective guide for health policy-making and improving parent–child adjustment in new generations.
Background. The higher education system of medical sciences in Iran requires competent and qualified educational leaders to enhance the quality of education, research, and social accountability. However, the process of selecting heads of educational departments and deans often lacks transparent, competitive, and competency-based mechanisms. This study aimed to identify the key competencies of educational leaders and to design context-specific, policy options for their selection in Iranian universities of medical sciences. Methods. This qualitative study was conducted in four phases using a mixed-methods design. In the first phase, a scoping review was performed to identify the competencies of educational leaders in national and international literature. In the second phase, qualitative data were collected through semi-structured interviews and focus group discussions with medical education experts and analyzed accordingly. In the third phase, the identified competencies were prioritized and weighted using the Delphi technique. In the fourth phase, findings from the previous phases were integrated, and policy options were developed based on the identified competency domains. Results. The competencies of educational leaders were categorized into four main domains: human resource management and development; organizational behavior and professional culture development; change management and educational innovation; and performance monitoring and evaluation. In the Delphi phase, these competencies were prioritized based on scientific, managerial, and professional ethics criteria. Emphasis was placed on selecting leaders through the participation of department members and requiring completion of relevant training programs. For each competency domain, a set of policy interventions was subsequently developed, including the establishment of a competency-based selection system, succession planning programs, continuous leadership development, and the implementation of data-driven performance evaluation systems. These interventions can be implemented as an integrated, phased policy package. Conclusion. Establishing a merit-based model for selecting educational leaders in Iranian universities of medical sciences is a strategic necessity. Designing and implementing a competency-based selection system as a priority action can facilitate the execution of complementary interventions and ultimately enhance transparency, accountability, and the quality of education within the national health system. Research Insights · Effective leadership of medical sciences universities is essential for improving educational, research, and organizational performance. It requires competencies beyond academic and scientific qualifications, including managerial, interpersonal, leadership, professional, and academic competencies. · Although existing evidence highlights the importance of these competencies, evidence on context-specific competencies and transparent, systematic criteria for selecting educational leaders in medical universities, particularly in Iran, remains limited. How these competencies can be translated into clear selection criteria remains insufficiently understood. · This study provides context-specific, evidence-informed, and merit-based policy options for selecting educational leaders in Iranian universities of medical sciences. The options organize the required competencies into a structured framework that can be applied to the selection process. · The proposed policy options can support Iranian universities of medical sciences in developing clearer and more systematic criteria for selecting educational leaders and in strengthening competency-based decision-making in educational leadership appointments.
Background. Waste management is essential, for improving urban services. Predicting the quantity of waste generated can play an important role in designing and optimizing the collection, transportation, and disposal processes. In this regard, machine learning techniques have been introduced as powerful tools for predicting the quantities of generated waste. Therefore, this study was conducted with the aim of predicting the quantity of municipal solid waste (MSW) using neural networks in Tabriz city, Iran. Methods. To predict the quantity of MSW, daily waste generation data from the Tabriz Municipality Waste Management Organization were used over a six-year period (2019–2024). The neural network employed consisted of an 8-layer LSTM network utilizing the Adam optimizer. The available data were divided into training and testing sets at an 85:15 ratio, and after the model training process, the predicted results were compared with the actual data to assess model accuracy. Root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were used to validate the proposed model. Results. The results indicated good accuracy of the designed model in predicting the trend and quantity of waste generation; specifically, the RMSE, MAE, and MAPE values for the training and testing data were calculated as 50.62 and 70.47 tons/day, 32.61 and 53.02 tons/day, and 3.52% and 5.86%, respectively. Conclusion. The analysis of the findings indicated the model's ability to reduce prediction deviation and increase reliability in estimating actual values. The low MAE values indicate that, on average, the model's prediction error compared to actual data was acceptable, and the model performed well in predicting the overall trend of waste generation. On the other hand, RMSE, which assigns greater weight to large errors, was also within a reasonable range, indicating that the model demonstrated good robustness against sudden fluctuations and outlier data. These results suggest that the trained model is capable of identifying hidden patterns in the time-series data and can be used as a suitable tool for data-driven prediction and management of municipal solid waste. Research Insights · Accurate prediction of municipal solid waste quantity, considering temporal fluctuations in waste generation, is essential for planning collection, processing, recycling, and disposal capacities and, ultimately, for improving sustainable waste management. · Conventional and traditional prediction methods may have limitations in accurately representing the complex patterns, temporal fluctuations, and nonlinear relationships involved in waste generation, which may reduce their ability to accurately predict waste quantities. This limitation highlights the need for more advanced, AI-based approaches for forecasting waste generation time series. However, the use of neural networks for predicting waste quantity involves challenges, including the model’s dependence on the accuracy and validity of the data, limited access to sufficient data, and difficulty in determining an optimal network architecture. Therefore, further evaluation of neural network–based models for predicting waste quantity using real-world data is needed. · In this study, an LSTM neural network was used to predict municipal solid waste quantity. Using daily municipal solid waste generation data from Tabriz, Iran, for the period 2019–2024, the LSTM model was trained to learn patterns in the data and predict waste quantity, and its performance was evaluated using RMSE, MAE, and MAPE. · The findings showed that the trained model was capable of identifying complex and hidden patterns in waste data and could be used as a data-driven decision-support tool for estimating future waste quantities. These findings add to the existing evidence on the application of AI-based approaches for predicting municipal solid waste quantity, particularly using real-world data from Tabriz, and may provide a basis for future studies using longer time periods and larger datasets.
Background. Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system in which an abnormal immune response leads to the destruction of myelin, axons, and neurons in the brain and spinal cord. During the month of Ramadan, Muslims abstain from eating, drinking, smoking, and sexual activity from dawn until sunset. The potential effects of Ramadan fasting on patients with MS remain a challenging clinical concern. This narrative review aimed to summarize the available evidence regarding the effects of Ramadan fasting in patients with MS. Methods. In this narrative review, a comprehensive search was conducted across PubMed, Scopus, Embase, and Web of Science databases. The search was conducted from database inception through the end of 2025 using the keywords (islam OR islamic OR ramadan OR muslim OR ramazan) AND fasting AND "Multiple sclerosis". A total of 56 articles were initially identified, of which 6 studies were included after screening. Eligible studies included those providing clinical evidence on evaluating the potential effects of Ramadan fasting in patients with MS. Animal studies and studies investigating other fasting-based dietary regimens (e.g., intermittent fasting) were excluded. Given the narrative nature of this review, no formal quality assessment of the included studies was conducted. Results. Based on six studies (two case-control studies and four cross-sectional studies), Ramadan fasting was not associated with an increased risk of MS relapse or worsening disability. The available evidence also suggests a beneficial association between Ramadan fasting and quality of life. However, higher levels of disability and longer disease duration were identified as factors associated with an increased risk of MS activation during Ramadan. Conclusion. Current evidence does not support the notion that Ramadan fasting is harmful to patients with MS, particularly those with mild disability. Moreover, fasting may be associated with improvements in quality of life among patients with MS. Nevertheless, these findings should be interpreted with caution, as the available evidence is derived from small studies conducted exclusively in the Eastern Mediterranean region. Research Insights · Multiple sclerosis (MS) is a chronic and disabling neurological disease, and Ramadan fasting represents an important clinical concern for many Muslim patients with MS. · This narrative review synthesized the available clinical evidence identified through searches of four major databases and included six studies, comprising two case-control and four cross-sectional studies. · Despite its clinical relevance, the available evidence remains sparse, fragmented, and largely based on small observational studies. · The available evidence suggests that Ramadan fasting is not associated with increased relapse or worsening disability in patients with MS, particularly those with stable disease and mild disability, and may be associated with improved quality of life. Future studies are needed to provide more definitive clinical recommendations.
